The text explores the transformative shift from traditional software development, known as Software 1.0, to a new paradigm termed Software 2.0, where artificial intelligence (AI) plays a central role. This transition is characterized by the use of deep learning models that generate code based on large data sets, rather than explicit programming by humans. Software 2.0 demonstrates significant advantages in processing unstructured data, such as images and text, and is being utilized in applications like content moderation, facial recognition, and predictive maintenance. However, it presents challenges, including data quality, diversity and bias, model explainability, and accuracy. The emergence of this AI-driven development also leads to new job roles, such as data scientists and ML engineers, requiring a shift in skill sets. While Software 2.0 is unlikely to entirely replace human software engineers, it is expected to significantly impact the field, necessitating new tools and methodologies to manage AI's integration into software development.